{
 "cells": [
  {
   "cell_type": "raw",
   "id": "f71a0dd6",
   "metadata": {},
   "source": [
    "**任务:多因子房价预测**\n",
    "基于task2_data.csv数据，建立多因子线性回归模型\n",
    "1、以面积、人均收入、平均房龄为输入变量，建立多因子模型，评估模型表现\n",
    "2、预测面积=150, 人均收入=60000, 平均房龄=5的合理房价"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a2d1d7c3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>面积</th>\n",
       "      <th>人均收入</th>\n",
       "      <th>平均房龄</th>\n",
       "      <th>价格</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>188.581619</td>\n",
       "      <td>79245.63626</td>\n",
       "      <td>4.901877</td>\n",
       "      <td>1.096850e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>164.161571</td>\n",
       "      <td>78936.74809</td>\n",
       "      <td>4.688919</td>\n",
       "      <td>1.455588e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>232.949602</td>\n",
       "      <td>63236.99563</td>\n",
       "      <td>4.878289</td>\n",
       "      <td>1.051696e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>150.608655</td>\n",
       "      <td>65122.34212</td>\n",
       "      <td>3.577503</td>\n",
       "      <td>1.373964e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>153.862555</td>\n",
       "      <td>63628.64511</td>\n",
       "      <td>5.877775</td>\n",
       "      <td>6.231222e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>165.454380</td>\n",
       "      <td>78251.30721</td>\n",
       "      <td>6.317630</td>\n",
       "      <td>9.624172e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>181.772344</td>\n",
       "      <td>63814.85840</td>\n",
       "      <td>5.296689</td>\n",
       "      <td>1.540739e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>172.055050</td>\n",
       "      <td>75195.11765</td>\n",
       "      <td>3.683635</td>\n",
       "      <td>1.442917e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>169.151184</td>\n",
       "      <td>63762.73947</td>\n",
       "      <td>6.168691</td>\n",
       "      <td>8.577471e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>217.052339</td>\n",
       "      <td>86801.37667</td>\n",
       "      <td>6.016151</td>\n",
       "      <td>1.543245e+06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           面积         人均收入      平均房龄            价格\n",
       "0  188.581619  79245.63626  4.901877  1.096850e+06\n",
       "1  164.161571  78936.74809  4.688919  1.455588e+06\n",
       "2  232.949602  63236.99563  4.878289  1.051696e+06\n",
       "3  150.608655  65122.34212  3.577503  1.373964e+06\n",
       "4  153.862555  63628.64511  5.877775  6.231222e+05\n",
       "5  165.454380  78251.30721  6.317630  9.624172e+05\n",
       "6  181.772344  63814.85840  5.296689  1.540739e+06\n",
       "7  172.055050  75195.11765  3.683635  1.442917e+06\n",
       "8  169.151184  63762.73947  6.168691  8.577471e+05\n",
       "9  217.052339  86801.37667  6.016151  1.543245e+06"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#数据加载\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "data = pd.read_csv('task2_data.csv')\n",
    "data.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "5e0dc8c9",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1440x360 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "fig = plt.figure(figsize=(20,5))\n",
    "fig1 = plt.subplot(131)\n",
    "plt.scatter(data.loc[:,'面积'],data.loc[:,'价格'])\n",
    "plt.title('Price VS Size')\n",
    "\n",
    "fig2 = plt.subplot(132)\n",
    "plt.scatter(data.loc[:,'人均收入'],data.loc[:,'价格'])\n",
    "plt.title('Price VS Income')\n",
    "\n",
    "fig3 = plt.subplot(133)\n",
    "plt.scatter(data.loc[:,'平均房龄'],data.loc[:,'价格'])\n",
    "plt.title('Price VS House_age')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "56d21091",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(5000, 3) (5000, 1)\n"
     ]
    }
   ],
   "source": [
    "#X y再次赋值\n",
    "X = data.drop(['价格'],axis=1)\n",
    "y = data.loc[:,'价格']\n",
    "X.head()\n",
    "\n",
    "#数据预处理\n",
    "X = np.array(X)\n",
    "y = np.array(y)\n",
    "y = y.reshape(-1,1)\n",
    "print(X.shape,y.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "52da3aab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#建立多因子回归模型 并且训练\n",
    "from sklearn.linear_model import LinearRegression\n",
    "model_multi = LinearRegression()\n",
    "model_multi.fit(X,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "62fd0fbc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1463868.24688829]\n",
      " [1445981.85185019]\n",
      " [1253388.6205439 ]\n",
      " ...\n",
      " [1285670.68139457]\n",
      " [1243839.71867445]\n",
      " [1116875.92416746]]\n"
     ]
    }
   ],
   "source": [
    "#多因子模型的预测\n",
    "y_predict_multi = model_multi.predict(X)\n",
    "print(y_predict_multi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "7c2edef9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "58264450329.883\n",
      "0.555093495178965\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import mean_squared_error,r2_score\n",
    "MSE_multi = mean_squared_error(y,y_predict_multi)\n",
    "R2_multi = r2_score(y,y_predict_multi)\n",
    "print(MSE_multi)\n",
    "print(R2_multi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "e60621e2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#可视化预测结果\n",
    "fig3 = plt.figure(figsize=(8,5))\n",
    "plt.scatter(y,y_predict_multi)\n",
    "plt.xlabel('real price')\n",
    "plt.ylabel('prdicted price')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "4b8d57c1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1037640.66671137]]\n"
     ]
    }
   ],
   "source": [
    "#预测面积=150, 人均收入=60000, 平均房龄=5的合理房价\n",
    "X_test = np.array([[150,60000,5]])\n",
    "y_test_predict = model_multi.predict(X_test)\n",
    "print(y_test_predict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c07982e6",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
